Energy detection is often used for spectrum sensing, applicable for cognitive radio systems, spectrum access, and resource communication management. Spectrum sensing using energy detection provides low complexity and rapid analysis, and requires no knowledge of transmission signal characteristics. The design and performance analysis of energy detection has been addressed under the assumption that the detection tests must be all independent. However, for energy detections conducted in a sliding window fashion, correlations among the detection tests need to be considered for evaluation of false alarm rates and detection probabilities for energy detections.
Thus, there is a need to overcome these and other problems of the prior art and to provide methods and devices for spectrum sensing using sliding window energy detection with correlated test statistics.